1. Field
At least one feature relates to digital communication systems, and more specifically, an improved turbo encoder having a low frame error rate.
2. Background
Communication systems use numerous techniques to increase the amount of information transferred while minimizing transmission errors. In these communication systems, the information is typically represented as a sequence of binary bits or blocks of bits called frames. The binary information is modulated to signal waveforms and transmitted over a communication channel. Communication channels tend to introduce noise and interference that corrupt the transmitted signal. At a receiver the received information may be corrupted and is an estimate of the transmitted binary information. The number of bit errors or frame errors depends on the amount of noise and interference in the communication channel.
To counter the effects of transmission channel corruption, error correction coding is often used in digital communication systems to protect the digital information from noise and interference and reduce the number of bit/frame errors. Channel coding is typically accomplished by selectively introducing redundant bits into the transmitted information stream. These additional bits allow detection and correction of bit errors in the received data stream thereby providing more reliable transmissions. One challenge is to achieve a low bit error rate, which translates to a low frame error rate, with an error correction coding scheme that is simple enough and fast enough to be implemented in hardware and/or software.
A well-known axiom in communications theory is that a randomly chosen code of sufficiently large block length n is capable of approaching the Shannon channel capacity limit. The maximum-likelihood (ML) decoding of such a code increases exponentially with n up to a point where decoding becomes physically unrealizable. Thus, another challenge is to develop error correction codes that have large equivalent block lengths, yet contain enough structure that practical decoding is possible.
One type of error correcting code is a parallel concatenated code, better known as turbo code, which is known to have a near-Shannon-limit error correcting performance. The basis of turbo coding is to introduce redundancy in the data to be transmitted through a channel. The redundant data helps to recover original data from the received data.
One implementation of a turbo code provides a parallel concatenation of two component convolutional codes or constituent encoders separated by a random interleaver. Partly due to the pseudo-random interleaver providing a “random” appearance, a turbo code can achieve a transmission performance to within 1 dB of the Shannon channel capacity. However, the problem in designing such interleaver is determining a scheme that rearranges the binary data to have a random appearance and thereby improve the distance spectrum of the transmitted redundant data therein.